基于CiteSpace的土壤法律研究可视化分析
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摘要
以Web of Science数据库为基础,对1987—2017年的文献进行可视化分析,旨在了解土壤法律研究领域的热点及发展趋势。结果表明:该领域国际上近三十年发文量呈递增趋势,我国在"土十条"颁布后发文量增长显著。发文主要集中在美国、中国、法国等国家,发文机构主要有中国科学院和美国农业部农业研究局。关键词共现图谱显示,土壤、模型、水、重金属、多孔介质、迁移、行为和流动等出现频率较高,归纳来看研究热点主要体现在模型在土壤研究中的应用、污染物的集中研究以及与土壤密切相关的其他领域研究。关键词共现时区分析发现,强度、去除、毒性、微量元素以及风险评价等代表了该领域的前沿研究内容和重要发展趋势。
Based on the database of Web of Science,visualization analysis is conducted on the literature from 1987 to 2017 in order to understand the hot-spots and development trends in the field of legal research on soil. The results showthat the amount of papers in this field has been increasing in the recent 30 years,and that of China has increased significantly after Ten Articles on Soil was issued. The published papers are mainly from USA,China and France,etc.,and the institutions that produced more papers mainly include Chinese Academy of Sciences and USDA Bureau of Agricultural Research. The keyword co-appearance network shows that soil,model,water,heavy metal,porous media,transport,behavior and flowhave had higher frequency. In summary,the research hot-spots mainly include the application of model in soil research,the concentrated study of pollutants and other fields closely related with soil. Time zone analysis of keyword co-appearance shows that strength, removal, toxicity, trace element and risk assessment represent the frontier research contents and important development trends in the field.
Based on the database of Web of Science,visualization analysis is conducted on the literature from 1987 to 2017 in order to understand the hot-spots and development trends in the field of legal research on soil. The results showthat the amount of papers in this field has been increasing in the recent 30 years,and that of China has increased significantly after Ten Articles on Soil was issued. The published papers are mainly from USA,China and France,etc.,and the institutions that produced more papers mainly include Chinese Academy of Sciences and USDA Bureau of Agricultural Research. The keyword co-appearance network shows that soil,model,water,heavy metal,porous media,transport,behavior and flowhave had higher frequency. In summary,the research hot-spots mainly include the application of model in soil research,the concentrated study of pollutants and other fields closely related with soil. Time zone analysis of keyword co-appearance shows that strength, removal, toxicity, trace element and risk assessment represent the frontier research contents and important development trends in the field.
引文
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[19]王景云,乔鹏炜,杨军,等.基于空间结构特征的土壤Cu、Pb来源解析——以北京市东南郊污灌区为例[J].植物营养与肥料学报,2018,24(1):195-202.
[20]崔锦霞,余振华,乔鹏炜,等.基于权重线性加和模型的城市污泥土地利用适用性评估[J].地球信息科学学报,2017,19(11):1514-1521.
[21]王蓓,张旭,李广贺,等.芦苇根系对土壤中石油污染物纵向迁移转化的影响[J].环境科学学报,2007,27(8):1281-1287.
[22]吴婷,李小平,蔡月,等.铅污染不同粒径土壤的重金属地球化学行为与风险[J].中国环境科学,2017,37(11):4212-4221.
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[24]张晓庆,徐丽,齐悦,等.紫松果菊对多环芳烃重污染土壤修复效能[J].生态学杂志,2018,37(2):492-497.
[25]王金满,郭凌俐,白中科,等.黄土区露天煤矿排土场复垦后土壤与植被的演变规律[J].农业工程学报,2013,29(21):223-232.
[26]蔡怡敏,陈卫平,彭驰,等.顺德水道土壤及沉积物中重金属分布及潜在生态风险评价[J].环境科学,2016,37(5):1763-1770.
[2]祖艳红,张慧,傅倩,等.基于Cite Space的学科领域研究热点与前沿可视化分析——以液体燃料在催化化学领域为例[J].复旦学报(自然科学版),2016,55(4):527-533.
[3]肖明,陈嘉勇,李国俊,等.基于Cite Space研究科学知识图谱的可视化分析[J].图书情报工作,2011,55(6):91-95.
[4]李峰,朱彬钰,辛涛.十五年来心理测量学研究领域可视化研究——基于CITESPACE的分析[J].心理科学进展,2012,20(7):1128-1138.
[5]李彬彬,许明祥,巩晨,等.国际土壤质量研究热点与趋势——基于大数据的Citespace可视化分析[J].自然资源学报,2017,32(11):1983-1998.
[6]Zheng J,Chen K H,Yan X,et al.Heavy metals in food,house dust,and w ater from an e-w aste recycling area in south China and the potential risk to human health[J].Ecotoxicology&Environmental Safety,2013,96(2):205-212.
[7]Li Z Y,Ma Z W,Kuijp T J V D,et al.A review of soil heavy metal pollution from mines in China:pollution and health risk assessment[J].Science of the Total Environment,2014(5):843-853.
[8]王欢欢.土壤污染治理责任溯及力研究[J].现代法学,2017,39(4):107-123.
[9]姬杰辉.GIS在土壤重金属污染防治制度设计中的作用[J].沈阳工业大学学报(社会科学版),2019,12(1):82-87.
[10]Bailón-Moreno R,Jurado-Alameda E,Ruiz-Ba R,et al.Analysis of the field of physical chemistry of surfactants with the Unified Scienctometric Model:fit of relational and activity indicators[J].Scientometrics,2005,63(2):259-276.
[11]拉巴,卓嘎,陈涛.藏北地区土壤水分遥感反演模型的研究[J].土壤,2017,49(1):171-176.
[12]叶勤,姜雪芹,李西灿,等.基于高光谱数据的土壤有机质含量反演模型比较[J].农业机械学报,2017,48(3):164-172.
[13]陈奕云,齐天赐,黄颖菁,等.土壤有机质含量可见——近红外光谱反演模型校正集优选方法[J].农业工程学报,2017,33(6):107-114.
[14]曹萌萌,杨圣舒,丁胜男,等.基于土壤反射光谱聚类分析的有机质预测模型[J].中国农业信息,2017(10):58-62.
[15]曾菁菁,沈春竹,周生路,等.基于改进LUR模型的区域土壤重金属空间分布预测[J].环境科学,2018,39(1):371-378.
[16]张厦,宋静,高慧,等.贵州铅锌冶炼区农田土壤镉铅有效性评价与预测模型研究[J].土壤,2017,49(2):328-336.
[17]吕佼佼,范文,吕远强.基于土壤侵蚀模型的浅层滑坡预警研究[J].水土保持通报,2017,37(3):227-230.
[18]谢云,岳天雨.土壤侵蚀模型在水土保持实践中的应用[J].中国水土保持科学,2018,16(1):25-37
[19]王景云,乔鹏炜,杨军,等.基于空间结构特征的土壤Cu、Pb来源解析——以北京市东南郊污灌区为例[J].植物营养与肥料学报,2018,24(1):195-202.
[20]崔锦霞,余振华,乔鹏炜,等.基于权重线性加和模型的城市污泥土地利用适用性评估[J].地球信息科学学报,2017,19(11):1514-1521.
[21]王蓓,张旭,李广贺,等.芦苇根系对土壤中石油污染物纵向迁移转化的影响[J].环境科学学报,2007,27(8):1281-1287.
[22]吴婷,李小平,蔡月,等.铅污染不同粒径土壤的重金属地球化学行为与风险[J].中国环境科学,2017,37(11):4212-4221.
[23]Rehman I U,Ishaq M,Ali L,et al.Enrichment,spatial distribution of potential ecological and human health risk assessment via toxic metals in soil and surface w ater ingestion in the vicinity of Sew akht mines,district Chitral,Northern Pakistan[J].Ecotoxicology and Environmental Safety,2018,154(1):127-136.
[24]张晓庆,徐丽,齐悦,等.紫松果菊对多环芳烃重污染土壤修复效能[J].生态学杂志,2018,37(2):492-497.
[25]王金满,郭凌俐,白中科,等.黄土区露天煤矿排土场复垦后土壤与植被的演变规律[J].农业工程学报,2013,29(21):223-232.
[26]蔡怡敏,陈卫平,彭驰,等.顺德水道土壤及沉积物中重金属分布及潜在生态风险评价[J].环境科学,2016,37(5):1763-1770.